Memories: Molecules and Circuits pp 99-112 | Cite as
The Organizing Principles of Real-Time Memory Encoding: Neural Clique Assemblies and Universal Neural Codes
Chapter
Abstract
Recent identification of network-level coding units, termed neural cliques, in the hippocampus has allowed real-time patterns of memory traces to be mathematically described, directly visualized, and dynamically deciphered. Those memory coding units are functionally organized in a categorical and hierarchical manner, suggesting that internal representations of external events in the brain are achieved not by recording exact details of those events but rather by re-creating its own selective pictures based on cognitive importance. These neural clique-based, hierarchical-extraction and parallel-binding processes enable the brain to acquire not only large storage capacity but also abstraction and generalization capabilities. In addition, activation patterns of the neural clique assemblies can be converted to strings of binary codes that would permit universal categorizations of the brain’s internal representations across individuals and species.
Keywords
Binary Code Place Cell Code Unit Neural Code Memory Encode
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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References
- Abbott LE, Sejnowski TJ (1999) Neural codes and distributed representations. Cambridge, The MIT PressGoogle Scholar
- Adrian EG (1926) The impulses produced by sensory nerve endings: Part 1. J Physiol 61:49–72PubMedGoogle Scholar
- Barlow H (1972) Single units and sensation: a doctrine for perceptual psychology? Perception 1:371–394PubMedCrossRefGoogle Scholar
- Bialek W, Rieke F (1992) Reliability and information transmission in spiking neuron. Trends Neurosci 15:428–433PubMedCrossRefGoogle Scholar
- Bliss TV, Collingridge GL (1993) A synaptic model of memory: long-term potentiation in the hippocampus. Nature 361:31–39PubMedCrossRefGoogle Scholar
- Eggermont JJ (1998) Is there a neural code? Neurosci Biobehav Rev 22:355–370PubMedCrossRefGoogle Scholar
- Fenton AA, Muller RU (1998) Place cell discharge is extremely variable during individual passes of the rat through the firing field. Proc Natl Acad Sci USA 95:3182–3187PubMedCrossRefGoogle Scholar
- Funahashi S, Bruce CJ, Goldman-Rakic PS (1989) Mnemonic coding of visual space in the monkey’s dorsolateral prefrontal cortex. J Neurophysiol 61:331–349PubMedGoogle Scholar
- Fuster JM (1973) Unit activity in prefrontal cortex during delayed-response performance: neuronal correlates of transient memory. J Neurophysiol 36:61–78PubMedGoogle Scholar
- Gross CG, Rocha-Miranda CE, Bender DB (1972) Visual properties of neurons in inferotemporal cortex of the macaque. J Neurophysiol 35:96–111PubMedGoogle Scholar
- Hebb DO (1949) The organization of behavior. Wiley, New YorkGoogle Scholar
- Leutgeb S, Leutgeb JK, Moser MB, Moser EI (2005) Place cells, spatial maps and the population code for memory. Curr Opin Neurobiol 15:738–746PubMedCrossRefGoogle Scholar
- Lin L, Osan R, Shoham S, Jin W, Zuo W, Tsien JZ (2005) Identification of network-level coding units for real-time representation of episodic experiences in the hippocampus. Proc Natl Acad Sci USA 102:6125–6130PubMedCrossRefGoogle Scholar
- Lin L, Osan R, Tsien JZ (2006) Organizing principles of real-time memory encoding: Neural clique assemblies and universal neural codes. Trends Neurosci 29:48–56PubMedCrossRefGoogle Scholar
- Markus EJ, Qin YL, Leonard B, Skaggs WE, McNaughton BL, Barnes CA (1995) Interactions between location and task affect the spatial and directional firing of the hippocampal neurons. J Neurosci 15:7079–7094PubMedGoogle Scholar
- Miller EK, Li L, Desimone R (1993) Activity of neurons in anterior inferior temporal cortex during a short-term memory task. J Neurosci 13:1460–1478PubMedGoogle Scholar
- McCulloch WS, Pitts W (1990) A logical calculus of the ideas immanent in nervous activity. 1943. Bull Math Biol 52:99–115; discussion 173–197PubMedGoogle Scholar
- O’Keefe J, Dostrovsky J (1971) The hippocampus as a spatial map. Preliminary evidence from unit activity in the freely-moving rat. Brain Res 34:171–175PubMedCrossRefGoogle Scholar
- Quiroga RQ, Reddy L, Kreiman G, Koch C, Fried I (2005) Invariant visual representation by single neurons in the human brain. Nature 435:1102–1107PubMedCrossRefGoogle Scholar
- Sanger TD (2003) Neural population codes. Curr Opin Neurobiol 13:238–249PubMedCrossRefGoogle Scholar
- Shamir M, Sompolinsky H (2004) Nonliner population codes. Neural Comp 16:1105–1136CrossRefGoogle Scholar
- Softky WR (1995) Simple codes versus efficient codes. Curr Opin Neurobiol 5:239–247PubMedCrossRefGoogle Scholar
- Thompson RF (2005) In search of memory traces. Annu Rev Psychol 56:1–23PubMedCrossRefGoogle Scholar
- Tsien JZ (2000) Building a brainier mouse. Sci Am 282:62–68PubMedGoogle Scholar
- Van Rullen R, Thorpe SJ (2001) Rate-coding versus temporal order coding: what the retinal ganglion cells tell the visual cortex. Neural Compt 13:1255–1283CrossRefGoogle Scholar
- Wigstrom H, Gustafsson B (1985) On long-lasting potentiation in the hippocampus: a proposed mechanism for its dependence on coincident pre-and postsynaptic activity. Acta Physiol Scand 123:519–522PubMedGoogle Scholar
- Wilson MA, McNaughton BL (1994) Reactivation of hippocampal ensemble memories during sleep. Science 265:676–679PubMedCrossRefGoogle Scholar
- Wood E, Dudchenko PA, Robitsek RJ, Eichenbaum H (2000) Hippocampal neurons encode information about different types of memory episodes occurring in the same location. Neuron 27:623–633PubMedCrossRefGoogle Scholar
- Zhou YD, Fuster JM (1996) Mnemonic neuronal activity in somatosensory cortex. Proc Natl Acad Sci USA 93:10533–10537PubMedCrossRefGoogle Scholar
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